Cloud EV Energy Usage Mapping Across Road Segments
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Solution Overview
Problem
Current systems lack an efficient method to aggregate and analyze energy usage data from electrified vehicles across multiple road segments and trips, limiting insights into energy consumption patterns and optimization opportunities.
Innovation Solution
A cloud-based system that collects and correlates vehicle-specific electric energy-related data from multiple electrified vehicles, including operational and ambient conditions, to generate crowd-sourced energy usage reports for road segments, enabling data analysis and statistical processing to inform energy consumption patterns and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If vehicle-specific electric energy-related data is collected from multiple electrified vehicles across multiple road segments and trips, then comprehensive energy consumption patterns and statistical insights are generated, but system complexity and data processing requirements increase
Solution Approach 1:
The patent combines energy consumption data from multiple vehicles, multiple road segments, and multiple trips into a unified cloud-based aggregation system. This merging approach enables comprehensive statistical analysis and pattern recognition that would be impossible with isolated vehicle data, directly resolving the contradiction by accepting system complexity as necessary to eliminate information loss about energy consumption patterns.
Solution Approach 2:
The cloud-based server performs multiple functions: data collection from diverse sources, correlation with road segment information, statistical analysis, and generation of energy usage reports. This multi-functional approach consolidates what would otherwise require separate systems into a single universal platform, managing complexity while maximizing information recovery.
2Measurement precision
If cloud-based server aggregates and analyzes data from plurality of vehicles for multiple road segments, then accurate energy usage reports are generated, but data transmission and processing time increase
Solution Approach 1:
The system pre-aggregates and analyzes energy consumption data across multiple vehicles and road segments before specific queries are made. By performing data correlation and statistical analysis in advance, the system reduces real-time processing requirements while maintaining high measurement precision in the generated energy usage reports.
Solution Approach 2:
The cloud-based server creates standardized energy usage reports that can be replicated and distributed to multiple users without requiring repeated analysis of the raw data. These report templates capture the essential energy consumption patterns and can be efficiently generated and shared, reducing overall processing time while preserving measurement accuracy.
Data Source
AI summary
The concepts described herein relate to methods, systems, and analytical techniques to achieve a cloud-based electrified vehicle energy usage system that includes a cloud-based server that is operative to receive vehicle-specific electric energy-related data from a plurality of connected electrified vehicles, and correlate the vehicle-specific electric energy-related data to a road segment. A data analysis is executed for the vehicle-specific electric energy-related data for the plurality of connected electrified vehicles for the road segment, and a crowd-sourced electrified vehicle energy usage report is generated for the road segment based upon the data analysis.